OpenDC 2.0: Convenient Modeling and Simulation of Emerging Technologies in Cloud Datacenters

Mastenbroek, Fabian; Andreadis, Georgios; Jounaid, Soufiane; Lai, Wenchen; Burley, Jacob; Bosch, J.D.; Eyk, Erwin van; Versluis, Laurens; Beek, Vincent van; Iosup, Alexandru

doi:10.1109/ccgrid51090.2021.00055

Cited by 21 publications

(9 citation statements)

References 42 publications

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“…Mastenbroek et al 15 re‐design and extend OpenDC 79 to support serverless computing. The low‐level nature of OpenDC naturally provides interchangeable interfaces but incurs higher complexity.…”

Section: Related Workmentioning

confidence: 99%

“…This then often leads to evaluations that do not allow generalizable conclusions about the performance of the systems under the wide variety of conditions that the edge‐cloud continuum provides. Simulators help to fill this gap by allowing quick iterations over ideas and evaluating their feasibility before deploying them on real‐world hardware 15 . They allow the creation of synthetic infrastructure according to specific parameters, such as deployment density in geo‐distributed settings or heterogeneity of compute nodes, 13 thereby vastly expanding the evaluation parameter space.…”

Section: Introductionmentioning

confidence: 99%

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faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms

Raith,

Rausch,

Furutanpey

et al. 2023

Softw Pract Exp

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This paper presents faas‐sim, a simulation framework tailored to serverless edge computing platforms. In serverless computing, platform operators are tasked with efficiently managing distributed computing infrastructure completely abstracted from application developers. To that end, platform operators and researchers need tools to design, build, and evaluate resource management techniques that efficiently use of infrastructure while optimizing application performance. This challenge is exacerbated in edge computing scenarios, where, compared to cloud computing, there is a lack of reference architectures, design tools, or standardized benchmarks. faas‐sim bridges this gap by providing (a) a generalized model of serverless systems that builds on the function‐as‐a‐service abstraction, (b) a simulator that uses trace data from real‐world edge computing testbeds and representative workloads, and (c) a network topology generator to model and simulate distributed and heterogeneous edge‐cloud systems. We present the conceptual design, implementation, and a thorough evaluation of faas‐sim. By running experiments on both real‐world test beds and replicating them using faas‐sim, we show that the simulator provides accurate results and reasonable simulation performance. We have profiled a wide range of edge computing infrastructure and workloads, focusing on typical edge computing scenarios such as edge AI inference or data processing. Moreover, we present several instances where we have successfully used faas‐sim to either design, optimize, or evaluate serverless edge computing systems.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms

Raith,

Rausch,

Furutanpey

et al. 2023

Softw Pract Exp

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“…OpenDC [36,46] is the simulation platform backing Capelin, enabling the capacity planner to model (FR1) and experiment (FR5) with the cloud infrastructure, interactively. The software stack of this platform is composed of a web app frontend, a web server backend, a database, and a discrete-event simulator.…”

Section: The Datacenter Simulatormentioning

confidence: 99%

“…We release our extensions of the open-source OpenDC codebase and the analysis software artifacts on GitHub 1 , as part of release 2.0 [46]. We conduct thorough validation and tests of both the core OpenDC and our additions, as detailed in Section 6.…”

Section: Software Prototypementioning

confidence: 99%

“…They also consider different operational factors such as the scheduler allocation policy, and phenomena such as correlated failures and performance interference [42,60,64]. 4) We release our prototype of Capelin, consisting of extensions to OpenDC 2.0 [46], as Free and Open-Source Software (FOSS), for practitioners to use. Capelin is engineered with professional, modern software development standards and produces reproducible results.…”

Section: Introductionmentioning

confidence: 99%

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Capelin: Data-Driven Capacity Procurement for Cloud Datacenters using Portfolios of Scenarios -- Extended Technical Report

Andreadis,

Mastenbroek,

van Beek

et al. 2021

Preprint

Self Cite

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Cloud datacenters provide a backbone to our digital society. Inaccurate capacity procurement for cloud datacenters can lead to significant performance degradation, denser targets for failure, and unsustainable energy consumption. Although this activity is core to improving cloud infrastructure, relatively few comprehensive approaches and support tools exist for mid-tier operators, leaving many planners with merely rule-of-thumb judgement. We derive requirements from a unique survey of experts in charge of diverse datacenters in several countries. We propose Capelin, a data-driven, scenario-based capacity planning system for mid-tier cloud datacenters. Capelin introduces the notion of portfolios of scenarios, which it leverages in its probing for alternative capacity-plans. At the core of the system, a trace-based, discrete-event simulator enables the exploration of different possible topologies, with support for scaling the volume, variety, and velocity of resources, and for horizontal (scale-out) and vertical (scale-up) scaling. Capelin compares alternative topologies and for each gives detailed quantitative operational information, which could facilitate human decisions of capacity planning. We implement and open-source Capelin, and show through comprehensive trace-based experiments it can aid practitioners. The results give evidence that reasonable choices can be worse by a factor of 1.5-2.0 than the best, in terms of performance degradation or energy consumption.

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CloudSim express: A novel framework for rapid low code simulation of cloud computing environments

Hewage,

Ilager,

Rodriguez

et al. 2023

Softw Pract Exp

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Cloud computing environment simulators enable cost‐effective experimentation of novel infrastructure designs and management approaches by avoiding significant costs incurred from repetitive deployments in real Cloud platforms. However, widely used Cloud environment simulators compromise on usability due to complexities in design and configuration, along with the added overhead of programming language expertise. Existing approaches attempting to reduce this overhead, such as script‐based simulators and graphical user interface (GUI) based simulators, often compromise on the extensibility of the simulator. Simulator extensibility allows for customization at a fine‐grained level, thus reducing it significantly affects flexibility in creating simulations. To address these challenges, we propose an architectural framework to enable human‐readable script‐based simulations in existing Cloud environment simulators while minimizing the impact on simulator extensibility. We implement the proposed framework for the widely used Cloud environment simulator, the CloudSim toolkit, and compare it against state‐of‐the‐art baselines using a practical use case. The resulting framework, called CloudSim Express, achieves extensible simulations while surpassing baselines with over a % reduction in code complexity and an 89.42% reduction in lines of code.

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OpenDC 2.0: Convenient Modeling and Simulation of Emerging Technologies in Cloud Datacenters

Cited by 21 publications

References 42 publications

faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms

faas‐sim: A trace‐driven simulation framework for serverless edge computing platforms

Capelin: Data-Driven Capacity Procurement for Cloud Datacenters using Portfolios of Scenarios -- Extended Technical Report

CloudSim express: A novel framework for rapid low code simulation of cloud computing environments

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